Abstract
Temporal, spatial and space-time scan statistics are commonly used to detect and evaluate the statistical significance of temporal and/or geographical disease clusters, without any prior assumptions on the location, time period or size of those clusters. Scan statistics are mostly used for count data, such as disease incidence or mortality. Sometimes there is an interest in looking for clusters with respect to a continuous variable, such as lead levels in children or low birth weight. For such continuous data, we present a scan statistic where the likelihood is calculated using the the normal probability model. It may also be used for other distributions, while still maintaining the correct alpha level. In an application of the new method, we look for geographical clusters of low birth weight in New York City.
Highlights
Spatial and space-time scan statistics [1,2,3,4] have become popular methods in disease surveillance for the detection of disease clusters, and they are used in many other fields
In most applications to date, the interest has been in count data such as disease incidence, mortality or prevalence, for which a Poisson or Bernoulli distribution is used to model the random nature of the counts
In papers published in 2008, Chen et al [5] studied cervical cancer mortality in the United States; Osei and Duker [6] studied cholera prevalence in Ghana; Oeltmann et al [7] looked at multidrug-resistant tuberculosis prevalence in Thailand; Mohebbi at al. [8] studied gastrointestinal cancer incidence in Iran; Rubinsky-Elefant et al [9] looked at human toxocariasis prevalence in Brazil; Frossling et al [10] evaluated the Neospora caninum distribution in dairy cattle in Sweden; Heres et al [11] studied mad-cow disease in the Netherlands; and Reinhardt et al [12] developed a system for prospective meningococcal disease incidence surveillance in Germany
Summary
Address: 1Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA, 2National Cancer Institute, Bethesda, MD, USA; Currently at the United States Food and Drug Administration, Rockville, MD, USA and 3New York City Department of Health and Mental Hygiene, New York City, NY, USA. Published: 20 October 2009 International Journal of Health Geographics 2009, 8:58 doi:10.1186/1476-072X-8-58.
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